Action Classification Algorithm Based on EGEI and LPP

摘要：

A foreground extraction algorithm based on background subtraction and edge detection was proposed to obtain the foreground with a little change. An action classification method based on Enhanced Gait Energy Image (EGEI) and Locality Preserving Projections (LPP) was used. The high dimensional feature space was non-linearly reduced to lower dimensional space, which outperformed PCA and 2DPCA. The nearest-neighbor classifier was adopted to distinguish different actions. This algorithm needn’t extract the period of the video, which was indispensable in some other methods. Experimental results show that the algorithm is simple, and achieves higher classification accuracy with less running time.

关键词： action recognition intelligent supervision Enhanced Gait Energy Image (EGEI) manifold learning locality preserving projections (LPP)

作者: Chunli Lin Shuxiang Guo Kejun Wang Chunli Lin Yu Xia Wansheng Cheng

作者单位: College of Automation Harbin Engineering University Harbin Heilongjiang 150001,China the School of the Higher Vocational Education University of Science and Technology Liaoning Anshan L

会议类型: 国际会议

会议名称: 2010 IEEE信息与自动化国际会议(ICIA 2010)

会议地点: 哈尔滨

会议语种:英文

页码: 1-5

在线出版日期: 2010-06-20（万方平台首次上网日期，不代表论文的发表时间）